Interference Alignment for MIMO Downlink Multicell Networks

Liu, Wei; Sun, Jiaxing; Li, Jiandong; Ma, Yu

doi:10.1109/tvt.2015.2477358

Cited by 19 publications

(11 citation statements)

References 23 publications

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“…In this section, we propose an advanced GEVD based grouping method aided IA scheme for the system model described in Section II with the configuration of N r = N t = N , i.e., the number of the receive antennas N r for each user is equal to the number of transmit antennas N t for each pico BS. Specifically, the macro users are divided into groups based on the GEVD grouping method proposed in [12]. The advantage of the proposed GEVD based grouping method aided IA scheme is that it can decrease the number of antennas required at the pico BS than that in the basic grouping method aided IA scheme and provide a higher maximum total achievable DoF than or equal to that of the basic grouping method aided IA scheme in the same configuration [12].…”

Section: Gevd Based Grouping Methods Aided Ia Schemementioning

confidence: 99%

“…Specifically, the macro users are divided into groups based on the GEVD grouping method proposed in [12]. The advantage of the proposed GEVD based grouping method aided IA scheme is that it can decrease the number of antennas required at the pico BS than that in the basic grouping method aided IA scheme and provide a higher maximum total achievable DoF than or equal to that of the basic grouping method aided IA scheme in the same configuration [12]. Similarly, there are also two scenarios to consider, i.e., K 2 is even or odd.…”

Section: Gevd Based Grouping Methods Aided Ia Schemementioning

confidence: 99%

“…We construct the (N r × d m )-dimensional receiver bemforming matrices U U U [2k −1,2] and U U U [2k,2] for the macro user [2k − 1, 2] and user [2k, 2], so that the ITI from the same pico BS to the macro users in Group k are aligned into the same subspace [12]. By this way, each pico BS just need to consider ITI on one effective macro user in each group instead of two macro users in the original scenario.…”

Section: A the Number Of Macro Users K 2 Is Evenmentioning

confidence: 99%

“…Furthermore, for the multiple cell uplink MIMO network, one IA scheme was proposed [11], where for each cell, the interference singals imposed by the users in the same cell are aligned into a low dimensional interference subspace [11]. Moreover, the generalized eigenvalue decomposition (GEVD) based grouping method aided IA scheme was proposed for downlink multi-cell networks [12]. Furthermore, for MIMO interfering broadcast channels (IBC), one IA scheme was investigated [13].…”

Section: Introductionmentioning

confidence: 99%

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Interference Alignment for MIMO Downlink Heterogeneous Networks

2020

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In this paper, we investigate the interference alignment schemes for the downlink of a heterogeneous network (HetNet), where the macro base station (BS) can serve arbitrary number of macro users. Furthermore, the number of data streams for macro users and pico users can be different. Firstly, we propose a basic grouping method aided interference alignment (IA) scheme and derive the transmit and receiver beamforming matrices in a closed-form expression. Furthermore, for the case where the number of antennas at pico BS is equal to the number of antennas at each user, we propose an advanced generalized eigenvalue decomposition (GEVD) based grouping method aided IA scheme which can reduce the number of transmit antennas required at the pico BS compared to the basic grouping method aided IA scheme. Moreover, we also derive the maximum total achievable degrees of freedom (DoF) for each scheme. In addition, it can be proved that the maximum total achievable DoF of the GEVD based grouping method aided IA scheme is higher than or equal to that of the basic grouping method aided IA scheme for the same configuration. INDEX TERMS Interference alignment, heterogeneous network, basic grouping method, GEVD.

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Section: Gevd Based Grouping Methods Aided Ia Schemementioning

confidence: 99%

Section: Gevd Based Grouping Methods Aided Ia Schemementioning

confidence: 99%

Section: A the Number Of Macro Users K 2 Is Evenmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Interference Alignment for MIMO Downlink Heterogeneous Networks

2020

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“…Another IA framework involving TDD channels is presented in [15]. In [16], interference alignment in MIMO downlink networks is investigated, where precoders are derived by eigen decomposition of the MIMO channels.…”

Section: Introductionmentioning

confidence: 99%

On the Application of K-User MIMO for 6G Enhanced Mobile Broadband

Yerrapragada

Kelley

2020

Sensors

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This paper presents a high-throughput wireless access framework for future 6G networks. This framework, known as K-User MIMO, facilitates all-to-all communication between K access points and K mobile devices. For such a network, we illustrate the demodulation of K2 independent data streams through a new interference cancellation beamforming algorithm that improves spectral efficiency compared to massive MIMO. The paper derives a multi-user Shannon Capacity formula for K-User MIMO when K is greater than or equal to 3. We define an Orthogonal Frequency Division Multiplexing (OFDM) frame structure that demonstrates the allocation of time-frequency resources to pilot signals for channel estimation. The capacity formula is then refined to include realistic pilot overheads. We determine a practical upper-bound for MIMO array sizes that balances estimation overhead and throughput. Lastly, simulation results show the practical capacity in small cell geometries under Rayleigh Fading conditions, with both perfect and realistic channel estimation.

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Model Transformation Based Closed-Form IA Design for Multiple-Cell MIMO Cellular Networks

Liu,

Song,

et al. 2024

Wireless Pers Commun

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Interference Alignment for MIMO Downlink Multicell Networks

Cited by 19 publications

References 23 publications

Interference Alignment for MIMO Downlink Heterogeneous Networks

Interference Alignment for MIMO Downlink Heterogeneous Networks

On the Application of K-User MIMO for 6G Enhanced Mobile Broadband

Model Transformation Based Closed-Form IA Design for Multiple-Cell MIMO Cellular Networks

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